用于三维空间避障的HDCS-RRT*算法机械臂 运动规划研究
Research on Manipulators Motion Planning with HDCS-RRT*Algorithm Applied to Obstacle Avoidance in 3D Space
刘春 1罗继祥1
作者信息
- 1. 湖北工业大学计算机学院,武汉 430068
- 折叠
摘要
针对RRT*算法应用于多自由度机械臂三维空间避障运动规划过程中存在的规划效率低、内存消耗大、规划效果不稳定等问题,提出一种启发式动态约束采样的RRT*(Heuristic dynamic constrained sampling-RRT*,HDCS-RRT*)算法.制定启发式动态采样域策略,通过目标偏向有界性的思想,提高算法收敛速度;设计自适应节点生成机制,根据障碍物环境调节新节点的生成方式,提高算法稳定性;通过冗余点检测,进一步优化路径成本.仿真与实验结果表明,相比于RRT*算法,改进后的算法规划速度更快,在狭窄区域的适应度良好,能够以低内存消耗和低时间成本生成较优的运动路径.
Abstract
To solve the problems in the application of RRT*algorithm in the process of obstacle avoidance motion planning for multi-DOF manipulators in 3D space,including low planning efficiency,large memory consumption and unstable planning result,a heuristic dynamic constrained sampling RRT*algorithm(HDCS-RRT*)is proposed in this paper.The algorithm devises a strategy of heuristic dynamic sampling domain,introduces the idea of goal-biased approach towards bounded to improve the convergence speed;it develops an adaptive node generation mechanism to adjust the generation mode of new nodes according to the obstacle environment,improves the stability of the algorithm;and the path costs are further optimized through redundant point detection.Simulation and experimental results show that the improved algorithm has faster planning,good adaptability in narrow areas,and can generate better motion paths with lower memory consumption and shorter path planning time than the RRT*algorithm.
关键词
运动规划/HDCS-RRT*/启发式动态采样域/自适应节点生成机制/冗余点检测Key words
motion planning/HDCS-RRT*/heuristic dynamic sampling domain/adaptive node generation mechanism/redundant point detection引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据